11/6/2017 15 Most Common Types of Data Visualisation — Datalabs

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15 Most Common Types of Data Visualisation »

via Payton Chung

The Most Common Type of DataVisualisations & Examples

15 Chart Types, Visualisations and How To UseThem

With the growing amount and accessibility of data, data visualisation is

becoming increasingly important. Not only does visualised data represent

large quantities of data coherently, it doesn’t distort what the data has to

say and helps the user discern relationships in the data. According to the

writers of A Tour Through the Visualization Zoo, “The goal of visualization

is to aid our understanding of data by leveraging the human visual system’s

highly-tuned ability to see patterns, spot trends, and identify outliers.”

In general, there are two basic types of data visualisation: exploration,

which helps nd a story the data is telling you, and explanation, which

tells a story to an audience. Both types of data visualisation must take into

account the audience’s expectations.

Within these two basic categories, there are many different ways data can

be made visual. In this article we’ll go through the 15 most common types

of data visualisation that fall under the 2D area, temporal,

multidimensional, hierarchical and network categories.

2D Area

2D area types of data visualisation are usually geospatial,

meaning that they relate to the relative position of things

on the earth’s surface.

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11/6/2017 15 Most Common Types of Data Visualisation — Datalabs

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via Eric Fischer

via Eric Fischer

1. Cartogram: A cartogram distorts the geometry or space of a map to

convey the information of an alternative variable, such as population or

travel time. The two main types are area and distance cartograms.

 

2. Choropleth: A choropleth is a map with areas patterned

or shaded to represent the measurement of a statistical

variable, such as most visited website per country or

population density by state.

 

3.

Dot Distribution Map: A dot distribution or dot density

map uses a dot symbol to show the presence of a feature

on a map, relying on visual scatter to show spatial

pattern.

 

Temporal

Temporal visualisations are similar to one-dimensional linear

visualisations, but differ because they have a start and nish time and

items that may overlap each other.

4. Connected Scatter Plot: A connected scatter plot is a

scatter plot, a plot that displays values of two variables for

a set of data, with an added line that connects the data

series.

 

5. Polar Area Diagram: A polar area diagram is similar to a

traditional pie chart, but sectors differ in how far they

extend from the center of the circle rather than by the size

of their angles.

 

6.

Time Series: A time series is a sequence of data points

typically consisting of successive measurements made over

a time interval, such as the number of website visits over a

period of several months.

 

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PhylogenyFigures

via Duke.edu

Multidimensional

Multidimensional data elements are those with two or more dimensions.

This category is home to many of the most common types of data

visualisation.

7. Pie Chart: A pie or circle chart is divided into sectors to

illustrate numerical proportion; the arc length and angle of

each sector is proportional to the quantity it represents.

 

8. Histogram: A histogram is a data visualisation that uses

rectangles with heights proportional to the count and

widths equal to the “bin size” or range of small intervals.

 

9. Scatter Plot: A scatter plot displays values for two

variables for a set of data as a collection of points.

 

Hierarchical

Hierarchical data sets are orderings of groups in which larger groups

encompass sets of smaller groups.

10. Dendrogram: A dendrogram is a tree diagram used to

illustrate an arrangement of clusters produced by

hierarchical clustering.

 

 

 

11. Ring Chart: A ring or sunburst chart is a multilevel pie

chart that visualises hierarchical data with concentric

circles.

 

 

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PhylogenyFigures

via Duke.edu

via Duke.edu

 

 

12. Tree Diagram: A tree diagram or tree structure

represents the hierarchical nature of a structure in graph

form. It can be visually represented from top to bottom or

left to right.

 

Network

Network data visualisations show how data sets are related to one another

within a network.

 

13. Alluvial Diagram: An alluvial diagram is a type of ow

diagram that represents changes in network structure over

time.

 

 

14. Node-Link Diagram: A node-link diagram represents

nodes as dots and links as line segments to show how a

data set is connected.

 

15. Matrix: A matrix chart or diagram shows the

relationship between two, three, or four groups of

information and gives information about said relationship.

 

Conclusion

As you can see, there is a plethora of options when it comes to data

visualisation, and these common types are only the tip of the iceberg.

 

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Chart via Digital Inspiration

 

Choosing the right type of visualisation depends on what you need to show

(comparison, distribution, composition, or relationship), how much detail

the audience needs, and what information the audience needs in order to

be successful.

Although the amount of data visualisation options may feel overwhelming,

whichever you choose will be much more comprehensible than raw

numbers alone.

 

UPDATE – We’ve got a new blog with 8 More CommonTypes Of Data Visualization. Click the link to read it.

 

Click the button below, ll out the form and they’re yours to download.

Datalabs' Guide To Charts

Related Posts:More Common of Types Data Visualizations

Data Visualisation Tools: A Curated List

The Need for Data Visualisation Skills

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